What patterns do you notice in the time series plot of average annual airfare from 2004 to 2018?
A. Horizontal pattern
B. Clear upward trend
C. Clear seasonal effects
D. Clear downward trend
Community Answer
By analyzing the time series plot of average annual airfare from 2004 to 2018, we would likely observe clear seasonal effects, indicating recurring patterns or fluctuations in airfare prices that occur at regular intervals within each year.(option c)
Drawing a time series plot of the average annual airfare from 2004 to 2018 in R language would likely reveal clear seasonal effects. Seasonal effects refer to recurring patterns or fluctuations that repeat at regular intervals over time, often corresponding to specific seasons or periods within a year.
Upon plotting the data, we may observe fluctuations in airfare prices that occur annually, such as increases during peak travel seasons (e.g., holidays, summer vacations) and decreases during off-peak periods. These seasonal patterns can manifest as repetitive peaks and troughs in the time series plot, indicating periods of higher and lower airfare prices throughout the year.
Additionally, the plot may also exhibit some level of variability or noise around the seasonal trends, reflecting other factors that influence airfare prices, such as changes in fuel costs, economic conditions, and airline industry dynamics.
The question probable maybe:
Question:
Year Airfare
2004 402.26
2005 391.5
2006 405.48
2007 390.3
2008 400.27
2009 359.91
2010 383.48
2011 402.45
2012 406.13
2013 407.99
2014 411.67
2015 395.7
2016 361.94
2017 352.85
2018 346.49
In R language,
- Conduct time series plot of the average airfare data. Question #1: What patterns do you notice in the time series plot of average annual airfare from 2004 to 2018? (a. horizontal pattern, b. clear upward trend, c. clear seasonal effects, d. clear downward trend)
Expert-Verified Answer
The patterns observed in the time series plot of average annual airfare from 2004 to 2018 are likely to include clear seasonal effects, indicating regular fluctuations in prices during certain times of the year. This pattern typically shows higher airfares during peak travel seasons and lower prices during off-peak periods. Therefore, the chosen option is C. Clear seasonal effects.
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Explanation
To analyze the time series plot of average annual airfare from 2004 to 2018, we need to observe the pattern and trends in the data. A time series plot visualizes how a variable changes over time, allowing us to identify trends and seasonal effects.
Considering the options:
A. Horizontal pattern - This would suggest that the airfare remained constant over the years, which is unlikely due to variations in demand and operating costs.
B. Clear upward trend - An upward trend indicates that prices have steadily increased over the years. This may not be supported by the data given that airfare can vary year-to-year due to economic factors, flight availability, and fuel prices.
C. Clear seasonal effects - Seasonal effects occur when there are predictable patterns at certain times of the year. In airfare pricing, this typically manifests as higher prices during peak travel seasons (e.g., summer vacation, holidays) and lower prices during off-peak seasons (e.g., winter months). This is a common trend in airline pricing and would align with fluctuations illustrated in a graph of annual airfares.
D. Clear downward trend - A downward trend would indicate a general decrease in flight prices over the years, which is also not likely considering the market dynamics.
Based on typical industry behavior, the most accurate choice would be C. Clear seasonal effects, as airfares tend to rise and fall with demand changes throughout the year, demonstrating predictable seasonal patterns. Thus, we expect to see repetitive peaks during high travel times and troughs during quieter periods in the time series data.
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Examples & Evidence
For instance, if the data shows higher airfare during summer months or around major holidays, this would support the idea of clear seasonal effects within the airfare pricing trend. A typical example is the increase in airfare prices around Thanksgiving or Christmas when travel demand significantly rises.
Studies on airfare trends often show patterns aligned with travel seasons, confirming the repetitive high and low price cycles based on time of year. Additionally, economic reports highlight these seasonal fluctuations as consistent across many years in the airline industry.
